Attempts have been made to create simulated neural circuits that include properties of biological neural circuits.
Biological neural circuits are made up of an incredibly dense meshwork of numerous, complex, tree-like units called “neurons.” Each neuron makes at least thousands of connections with other neurons. It is at these connections or “synapses” that information is transferred between the neurons. The pattern of these connections, that is the wiring of the neural circuit, in large part defines the circuit's function. The sensory performance of biological organisms makes it clear that such circuitry is capable of very sophisticated and powerful processing. However, unlike conventional electronic circuits, this extraordinary meshwork wires itself. That is to say, the pattern of synaptic connections in the neural circuit is not determined a priori with an explicitly encoded point-to-point wiring diagram, but instead is formed through mechanisms that allow self-organization of the circuit as part of the functioning of the neurons. The pattern of wiring embeds information imparted both genetically as well as that learned by exposure to the sensory environment. This process of wiring may continue throughout the life of the organism. All real neural circuits wire themselves. Therefore, in seeking to create simulated neural circuits which emulate some of the function of these biological circuits, it may be advantageous to generate simulated circuits that also wire themselves. After such simulated circuits have been generated, they subsequently may be implemented and fabricated, for example, as integrated circuits, for real-life applications.